HIGH STAKES, HIGH REWARDSimages.forbes.com/forbesinsights/ey_data_analytics_2017/Advanced... · stumbling blocks that inhibit a more sophisticated use of advanced analytics. For example,

ANALYTICS

CONSUMPTION

MARKET

STRATEGY

A N A L Y T I C S L I N K A G E S

INITIATIVES

ANALYTICS

PRODUCTION

OUTCOMES

COMPETITIVEDIFFERENTIATION

OPERATINGMODEL

INITIATIVEDESIGN

MEASUREMENT& LEARNING

INTERVENTIONDESIGN

DATA & ADVANCED ANALYTICS

INDIAN ENTERPRISES OUTPERFORM GLOBAL PEERS

HIGH STAKES, HIGH REWARDS

TABLE OF CONTENTS

3

4

7

10

13

16

19

22

FOREWORD

EXECUTIVE SUMMARY

COMPETITIVE DIFFERENTIATION

OPERATING MODEL

INITIATIVE DESIGN

INTERVENTION DESIGN

MEASUREMENT AND LEARNING

CONCLUSION

2 | © 2017 EYGM LIMITED. ALL RIGHTS RESERVED.

It gives me immense pleasure to share

compelling insights on how Indian enterprises

have outperformed global peers in their

commitment to use advanced analytics for

critical business decisions. According to the

study, jointly conducted by Forbes Insights and

EY, there is an increasing trend of companies,

proficiently using data and analytics for new

business initiatives, to register high growth

in revenues and profits—hitting 15% or more,

with significant improvement in their risk

profile. The study is based on a C-suite survey

of nearly 200 Indian companies, with annual

revenues ranging between $500 million and

$50 billion, approached by Forbes Insights

between August and September of 2016.

Clearly, Indian enterprises are setting an

example for the world to follow, while also

learning from global counterparts who see

competitive advantage in the use of advanced

analytics more effectively. Already, there is a

growing impetus on Analytics services and

organisations worldwide are now realising

their direct impact on business performance,

but Indian companies are proving to be the

frontrunners in this area. It is heartening to

find that more than a third of Indian executives

vouch for having a well-established analytics

strategy, which forms the core of their overall

business strategy. Therefore, as no surprise,

this puts them ahead of leaders from all parts

of the world—only 23% of enterprises overall

have reached a similar level of analytics

evolution.

I am overwhelmed to discover that executives

in India are targeting resources to better

understand the business opportunities, as

well as the risks, associated with the five

‘Synapses’ i.e. competitive differentiation,

operating model, initiative design,

intervention design and measurement and

learning, as identified in the report. The report

has also brought forth interesting insights

on Indian firms excelling at having well-

established analytics strategies that are key

to the overall business growth. However, the

management committee needs to ensure a

smooth flow of collaboration and alignment

across the enterprise and departments which

has currently been one of the biggest reasons

for the analytics projects to succeed or fail.

I encourage each one of you to read the

complete report and ask EY about what

leading organizations in India are doing to

create a competitive advantage through

analytics, and how we can help yours.

FOREWORD

Gautam Bhattacharya

Partner and National Analytics Leader, EY India

+91 806 727 5144

[email protected]

HIGH STAKES, HIGH REWARDS: FOREWORD | 3


EXECUTIVE SUMMARY

A recent survey of global enterprises shows

direct linkage between proficiency in data and

advanced analytics and business performance.

Companies that are most adept at using

data for new business initiatives are more

likely to register high growth in revenues and

profits—hitting 15% or more--while also seeing

significant improvement in their risk profile.

The research conducted by Forbes Insights

and EY found significant regional trends, as

well, including analytics as one of the key

pillars of organizational maturity. For example,

Indian firms by far outperformed their global

peers in the use of advanced analytics by

senior executives.

But while Indian enterprises are leading in

some areas, as a group they also struggle

with other important elements of advanced

analytics strategies, such as fostering closer

collaboration among technical and business

stakeholders. Clearly, executives in the Indian

subcontinent have much to teach—and learn—

from counterparts throughout the world

who see a competitive advantage in using

advanced analytics most effectively.

A top priority for enterprises in India and

elsewhere is overcoming problems that arise

between the crucial steps organizations take

as they move from identifying new business

opportunities, acting on insights and then

measuring the outcomes of their data-driven

strategies. We liken them to “synapses” in the

brain, where communications pass from one

cell to another.

The difference is that, in the brain, these

communications pass naturally from cell to

cell, while in large enterprises the smooth

flow of information isn’t automatic. The EY-

Forbes Insights research shows that the way

global enterprises handle these junctures

translates into business success and defines

clear stratifications in analytics maturity.

For example, the top performers in the

overall survey who have translated analytics

strategy into well-designed initiatives are

considerably more likely to enjoy growth in

operating margins and revenues of 15% or

more, respectively, along with significant

improvement in their risk profile.

HIGH STAKES, HIGH REWARDS: EXECUTIVE SUMMARY | 5

Findings from the global survey also show sophisticated users of advanced analytics

experience additional benefits:

They can capitalize on artificial intelligence and other forms of predictive and

prescriptive modeling for insights about possible future outcomes and ways to

address them

Because leaders incorporate advanced analytics early in the business development

processes, they can deliver better outcomes by shaping initiatives based on actual

data rather than gut instinct

Leaders can accurately measure business value to demonstrate the impact—and

validity—of their investments in advanced analytics

ANALYTICS LINKAGES

OUTCOMES

MEASUREMENT AND LEARNING Quantifying and learning from

data-driven business outcomes.

OPERATING MODEL Building the underlying models that govern analytics activities, such as organizational structures that allow

collaboration, chain of command, etc. INITIATIVE DESIGN

Defining the specific activities and projects that will achieve desired

business outcomes

INTERVENTION DESIGNTranslating all the upfront goal-setting,

modeling, and methodology into action— making analytics insights an integral part of business operations.

COMPETITIVE DIFFERENTIATIONDefining the role that data and analytics plays in the company strategy and business model.

STRATEGYINITIATIVES

ANALYTICSPRODUCTION

ANALYTICSCONSUMPTION

MARKET

70%of these leaders have used advanced analytics to overhaul business strategies and update how they compete in their respective markets

75%operate a full range of enterprise, departmental, and line-of-business analytics groups that operate within a well-aligned framework


METHODOLOGY

This report is based on a survey

of nearly 200 Indian companies

conducted in August and September

2016 by Forbes Insights. Respondents

are C-level executives, including

chief executives, presidents, and

CIOs. Industries represented include

banking, healthcare, technology, and

telecommunications. Organizations

surveyed had at least $500 million in

annual revenues, and 28% had revenues

of more than $50 billion.

However, the global study also found

stumbling blocks that inhibit a more

sophisticated use of advanced analytics. For

example, one common pain point is a lack

of collaboration among business units and

analytics specialists when defining desired

outcomes, designing operational models, and

measuring the results. Without this cross-

department cooperation, the goal of turning

analytical insights into action can break down

at any stage of the process.

To overcome these hurdles, executives in India

are targeting resources to better understand

the business opportunities, as well as the risks,

associated with each of these five synapses.

For example, an issue common to each of

the synapses is a lack of collaboration among

business units and analytics specialists.

This can derail attempts to define desired

outcomes, design operational models, and

measure the results of analytics strategies.

The survey results highlight best practices

specific to each synapse to help executives

avoid common stumbling blocks and derive

long-term value from data initiatives. In

addition, we present insights from Indian

executives who explain the unique challenges

of competing in this dynamic market and

why analytics success is vital to their ongoing

success.

HIGH STAKES, HIGH REWARDS: COMPETITIVE DIFFERENTIATION | 7

KEY FINDINGS

• Indian firms excel at having well-established analytics strategies that are central to the overall business strategy

• Many executives in India view advanced analytics as a strategic resource

• But the lack of collaboration and alignment within the management committee blocks success

Having a mature advanced analytics strategy has

a direct link to business performance, and Indian

companies as a group are distinguishing themselves

in this area. More than a third of Indian executives say

their company’s analytics strategy is well established

and central to the overall business strategy. As a group,

this puts them ahead of leaders from all parts of the

world, wherein only 23% of enterprises overall have

reached a similar level of analytics evolution.

Furthermore, 34% of Indian organizations report that

their advanced analytics strategy is starting to be

viewed as a key strategic priority, edging out the 30%

of global peers that share this viewpoint.

Analytics maturity has ripple effects. More than a

quarter (26%) of Indian executives say advanced

analytics have completely changed their business

strategy and how they compete, with another 39%

only slightly behind—they report changes to significant

elements of their strategy. Again, this put them

ahead of the global pace, with only 17% of enterprises

saying they already have completely changed business

strategies while 33% are seeing significant elements

being impacted.

“Data and analytics are like the headlights of a car, not

the taillights,” says Rajesh Mishra, vice president of

finance and supply chain for Pernod Ricard Travel Retail

Americas. “Using analytics for competitive differentiation

isn’t about analyzing past performance, its value is in

giving you a direction for the future.”

Across organizations worldwide, advanced analytics

proficiency is making the biggest changes in how

firms target and segment customers, something that is

also playing out in India. Thirty-five percent of Indian

executives have seen complete changes in this area,

which is 10% more than at organizations worldwide.

Similarly, nearly a third of Indian companies are also

using analytics to stay ahead of rapidly changing

customer taste.

But not all the news coming from India is positive.

Problems arise over how people perform their respective

roles and interact with corporate peers. Some of the

biggest challenges—which each impact more than a third

COMPETITIVE DIFFERENTIATION

STRATEGY

MARKET


Regulatory constraints prevent us from acting 51%

Organization, culture and decision-making based more on intuition than data 48%

Lack of collaboration/alignment among members of the management committee 46%

Lack of budget and other forms of organization commitment 43%

Lack of senior leadership support 38%

No appetite for a major transformation that would result from data and analytics-driven strategies 27%

We have not had the right leader to serve as a catalyst for change 26%

Data and analytics is not changing our business strategy 7%

WHAT BEST DESCRIBES THE ROLE OF DATA AND ANALYTICS IN THE BUSINESS STRATEGY IN YOUR ORGANIZATION?

WHAT ARE YOUR TOP PAIN POINTS WHEN IT COMES TO DEVELOPING OR REFINING THE BUSINESS STRATEGY TO ACCOUNT FOR DATA AND ANALYTICS?

Analytics strategy is well established and central to the overall business strategy

Analytics strategy is establishedand starting to be viewedas a key strategic priority

Analytics strategy is established forthe enterprise, but not fully alignedacross the business

Some analytics strategy existsfor functionsor lines of business

No analytics vision orstrategy existsat this timeNote: Due to rounding, numbers presented may not total 100

37%

34%

15%

12%

1%

182 TOTAL

HIGH STAKES, HIGH REWARDS: COMPETITIVE DIFFERENTIATION | 9

RECOMMENDATIONS

1 Create a data and advanced analytics strategy that

balances enterprise goals with the needs of each

business unit, including any unique regulatory and

business requirements.

2 Create a compelling business case that demonstrates

the key role advanced analytics plays for competitive

differentiation in today’s digital marketplace.

3 Show the direct link between advanced analytics

and business value and use this to convince the C-Suite

and Board to make analytics a top priority for the

enterprise.

4 To identify new business opportunities and how they

can be supported with advanced analytics, foster closer

collaboration among stakeholders from all departments.

of Indian organizations—are lack of commitment to

data-based decision-making or organizational support

for data-driven cultures, which impair the competitive

differentiation and operating model synapses. This

problem illustrates how companies still struggle with

intuition-based decision-making, where executives

favor “gut feel” more than fact-based decisions.

OVER THE NEXT TWO YEARS, NEARLY THREE-QUARTERS OF THEM PLAN TO INVEST

$10 MILLION OR MORE FOR DATA AND ANALYTICS RESOURCES.

"WE HAVE SPONSORSHIP FROM

TOP-LEVEL EXECUTIVES, AND

THAT IS A SIGNIFICANT REASON

WHY WE’RE SUCCESSFUL."

KRISHNAKUMAR RAMASUBRAMANIANHEAD OF BUSINESS INTELLIGENCEAND ANALYTICS, MAX LIFE INSURANCE

Related to this is a widespread lack of collaboration

and alignment within the management committee,

which also impedes the smooth flow of information

during each of the synapse transition points.

To better utilize data and advanced analytics for

strategic gain, enterprises must foster a cultural

shift designed to promote collaboration and data

analytics skills. Collaboration between analytics

specialists and business people also overcomes

traditional cultures where there’s overreliance on

gut-feel decision making.

Data leaders point to one other vital element for

promoting collaboration. “We have sponsorship

from top-level executives, and that is a significant

reason why we’re successful,” says Krishnakumar

Ramasubramanian, head of business intelligence and

analytics at Max Life Insurance, a large carrier based in

India.

Looking beyond cultural considerations, Indian

business leaders appear to understand the financial

commitments needed to successfully infuse business

initiatives with data and analytics. Over the next two

years, nearly three-quarters of them plan to invest

$10 million or more for data and analytics resources.

This shows a growing financial commitment to data

and analytics--in the past two years, only about half of

the companies spent similar amounts.

Indian companies still have work to do when it comes

to advancing their data and analytics strategies. But

recognizing lingering cultural and collaboration issues

and making appropriate financial investments will keep

firms moving in the right direction.


KEY FINDINGS

• Nearly half of Indian firms already have an enterprise-wide advanced analytics strategy

• But many Indian companies struggle with advanced analytics governance policies

• A priority in India is expanding training to improve the creation of operating models

Smooth collaboration among stakeholders is also essential

for effective operating models, which provide frameworks

for enabling enterprise, departmental, and line-of-business

analytics to work together. Unfortunately, only a little

more than a quarter of Indian enterprises see this level

of governance in their organizations. Most see progress

only within certain departments and business lines or say

enterprise-level data and advanced analytics groups are

still emerging.

Related to this is the ability of organizations to implement

enterprise-wide data governance standards, something

that’s being accomplished by 40% of the leaders in

India. This is important for fostering greater trust in the

accuracy and security of corporate data. “In the past,

most of our decisions were based on gut feeling, but as

we’re maturing, we’re moving to a point where we are

relying more and more on data to inform our decisions,”

says Chetan Agarwal, executive vice president of IT at

Lodha, a real-estate developer based in Mumbai.

WHICH BEST DESCRIBES YOUR ORGANIZATION'S CURRENT STATUS REGARDING THE ORGANIZATION AND GOVERNANCE OF DATA ANALYTICS?

36% 28% 22% 13%

1%

Data and analytics groups are well-established

in departmentsor lines of business

Enterprise, department and

lines-of-business data and analytics

groups exist and are well-aligned

Enterprise-level data and

analytics group are emerging

Some informal data analytics

groups exist in departments or

lines of business

No organization

exists

OPERATING MODEL

INITIATIVESSTRATEGY

HIGH STAKES, HIGH REWARDS: OPERATING MODEL | 11

He adds that reliance on analytics increases as people

become more confident in the quality of corporate data,

which comes from having solid policies around data

management.

The close alignment of data and analytics teams is a

foundation for effective operating models. Forty-nine

percent of Indian companies use their enterprise analytics

teams to create an organization-wide strategy for

data and analytics. This is important for many reasons,

including because it demonstrates a commitment by

senior executives to having data-driven approaches that

underlie business initiatives going forward.

The research shows that to improve operating models

going forward, Indian leaders must expand training and

make data and advanced analytics a part of operating

models. To do this, organizations should focus more

ENTERPRISE ANALYTICS

closely on recruiting, developing and retaining individuals

who can serve as analytics “leaders” in various parts of

the business. Executives should also define what it means

to the organization to have more of an analytics mindset

and culture. No operating model will succeed long term

without corresponding focus on creating a culture where

analytics practitioners can apply their craft and thrive.

Increasing adoption rates among employees is another top

priority for enhancing analytics maturity. To promote wide

acceptance and adoption of advanced analytics among

business people, the resource must be accessible and easy

to use. This means offering tools that present findings

in highly visual formats that are well integrated within

the primary applications business people use to perform

their jobs. After all, if a solution is difficult to navigate and

presents information that’s not clear to a business user,

they’ll be less likely to adopt it.

74%

Technology

Selecting,

implementing,

managing

common

technology

platform and

tools

51%

Development

Building models

and other assets

that can be

leveraged across

the business

49%

Strategy

Setting the

overall firm-level

data and

analytics

strategy and

plan

40%

AdvancedAnalytics

Analytics

Working on use

cases that

require skills not

resident in the

businesses

40%

Data

Implementing

data gover-

nance/standards

used across the

organization

17%

PortfolioManagement

Management

Selecting

projects, making

investment

allocation

decisions

12%

Measurement

Putting in place

standards for

value measure-

ment,

If your organization uses some form of enterprise-level analytics team

(in addition to capabilities that exist within business units),

what is the primary purpose of this team?

RECOMMENDATIONS


1 Clearly define an operating model that brings

advanced analytics resources close to each line of

business and function.

2 Support the model with an enterprise-level analytics

team charged with setting the overall strategy for data

and advanced analytics.

3 The team should also implement enterprise-wide

data governance standards to foster greater trust in the

accuracy and security of corporate data.

WHAT ARE YOUR TOP PAIN POINTS WHEN CREATING A DATA AND ANALYTICS OPERATING MODEL?

Lack of training across functions

31%

Data and analytics has not historically

been part of an operating model

30%

Lack of adoption/engagement by employees

29%

Lack of change management acumen

28%

Lack of alignment/collaboration across functions

27%

Lack of data and analytics proficiency

within many functions

27%

Lack of data/knowledge management sharing

26%

A data and analytics operating model would

disrupt existing models too much

24%

Lack of data and analytics leaders at the

business-unit level

24%

Lack of vision/buy-in from top

levels of management

20%

Technology is not integrated

20%

We do not have mature data and analytics

15%

HIGH STAKES, HIGH REWARDS: INITIATIVE DESIGN | 13

KEY FINDINGS

• Improving partner and vendor relationships are top goals for advanced analytics initiatives in India

• Executives must better align the IT department, the data and advanced analytics team, and business peopleto improve data strategies

When executives reach the point of designing the

specifics of business initiatives, they must make a series

of critical decisions that will guide their use of data

and advanced analytics and ultimately determine the

success of the project. This starts with defining the

specific business outcomes leaders hope to achieve.

The goals that ranked highest among Indian

respondents were increased quality and more targeted

interactions with partners and vendors. Indian

executives cited this area in greater numbers than their

global peers, showing partner and vendor relationships

is a clear regional concern in the subcontinent.

Other goals show a bias toward practical matters, such

as the desire for increased sales or revenues and higher

rates of customer satisfaction. The high rankings aren’t

surprising, after all, they’re the main focus of business

executives everywhere. But progressive leaders are

also looking to employ advanced analytics in strategic

ways, too. Twenty-eight percent see opportunities for

developing new products and services with the aid of

advanced analytics.

It will take more than just an attitudinal change to move

these companies forward. Behind the scenes, they must

also significantly improve their methods for developing

initiative designs. However, this is another area where

Indian firms appear to be ahead. An impressive 71%

of the respondents say they always or very often use

consistent methods for data and analytics initiative

designs. Globally, just 47% of executives report this level

of consistency.

Indian respondents have another advantage—36% say

their data and analytics and business groups work

together highly effectively. Only 16% globally share this

status.

But Indian companies have work to do in other areas.

Nearly half of them say a top pain point is the lack

of alignment among the IT department, the data and

analytics team, and business people. A similar number

report trouble from a lack of people with analytics skill

sets to define an appropriate approach to designing

analytics initiatives. In addition, many say problems arise

because desired business outcomes are not well defined

at the start.

INITIATIVEDESIGN

ANALYTICSPRODUCTION

INITIATIVES

Enable common enterprise view of customers

Encourage rapid and constant innovation

More effectively deploy our people

Accelerate decision-making

Transform operating modelsIncre

ase

qualit

y a

nd m

ore

tar

get

ed in

tera

ctio

ns w

ith p

artn

ers a

nd vendors

33%

Incre

ase

sale

s or

reve

nues

30%

Dev

elo

p n

ew p

roduct

s/se

rvic

es

28%

Incre

ase c

ust

om

er s

atis

fact

ion/

rete

ntio

n

27%

Imp

rove

curr

ent pro

duc

ts/s

ervi

ces

26%

Imp

rove

and s

trea

mlin

e in

tern

al o

pera

tions/c

ut costs 23%

Dee

per

mar

ket in

sigh

ts

21%

Tran

sform

bus

ines

s m

odels

2

1%

19%

19%

19%

15%

14%


WHAT SPECIFIC BUSINESS OUTCOMES IS YOUR ORGANIZATION TRYING TO ACHIEVE THROUGH THE APPLICATION OF DATA AND ANALYTICS?

HOW OFTEN DO YOU USE CONSISTENT METHODS/APPROACHES FOR DATA AND ANALYTICS INITIATIVE DESIGN (PROJECTS TARGETING A SPECIFIC USE CASE)?

0

10

20

30

40

50%

SOMETIMES5%

27%ALWAYS

FAIRLY OFTEN22%

1%NEVER

44%VERY OFTEN

Note: Due to rounding, numbers presented may not total 100

RECOMMENDATIONS

HIGH STAKES, HIGH REWARDS: INITIATIVE DESIGN | 15

Lack of collaboration between IT, data and analytics team and the business team 46%

Lack of people with analytics skill sets to define an appropriate to approach the problem 46%

Desired business outcomes not well defined at the start 40%

Technology needs not considered early enough 38%

Lack of clear and engaged sponsorship 36%

Lack of consistent methods/processes 35%

Unclear responsibilities across functions 33%

Not enough focus on who the ‘user’ will be and how the analytics will change what they do 25%

Other 1%

WHAT ARE YOUR TOP PAIN POINTS WHEN DESIGNING DATA ANALYTICS INITIATIVES?

1 Develop and apply consistent processes and a

common nomenclature for designing advanced

analytics initiatives. This should be balanced

with creating an environment for cost effective

experimentation and investigation, which allows teams

to ultimately choose the best use cases.

2 Ensure that stakeholders define strategic objectives

and desired business outcomes and closely align

proposed initiatives to these goals. Focus on a better

definition of a strategic outcome such as driving

better engagement with customers. That goal should

then translate into initiatives that evaluate, streamline,

improve or otherwise reimagine customer engagement

across all channels.

3 Carefully think through the competencies and roles

that are needed across analytics, IT and business teams

– ensure there is joint responsibility and accountability

for addressing a specific initiative. Assess the current

skills across these teams to ensure that the right mix

actually exists to drive initiatives in a way consistent with

industry-leading practices.


KEY FINDINGS

• Earlier is better when applying advanced analytics to business development

• Indian executives are ahead of their global peers in the use of advanced analytics among senior business leaders

• Lack of skills is a significant roadblock to activating analytical insights

Intervention design is when stakeholders translate

goal-setting, modeling, and methodology development

into new business decisions or processes. Critical

for success at this stage is determining when in the

development process companies design how to apply

analytics to best realize the value of their efforts. Doing

so as early in the process as possible is ideal since this

allows the most time for validating initiatives based

on available data, rather than simply relying on gut

feel. However, only 29% of Indian executives claim

this level of early intervention, while about a quarter

of respondents say deciding how to apply analytics

comes after starting data collection and knowing what’s

possible. Another 28% say they make this decision only

after they know what type of analytics will be applied.

Sixteen percent overall still wait until after they’ve built

their models, indicating an area that requires further

attention.

On the plus side, Indian firms are ahead of those in other

regions in the use of data and analytics among senior

business leaders. Fifty-seven percent of top executives in

India turn to data and analytics for more than half of their

decision-making. This contrasts with international results,

where only 45% of senior executives show a similar

commitment to analytics. The bottom line: executives in

India are more likely to capitalize on advanced analytics

for decision-making than their counterparts in other

countries.

When senior executives see the competitive advantages

of analytics and lead by example, it encourages people

throughout the organization to use analytics more

extensively, says Rahul Shandilya, senior vice president of

IT and analytics for the automotive and farm equipment

sectors at Mahindra and Mahindra in Mumbai.

INTERVENTION DESIGN

ANALYTICSPRODUCTION

ANALYTICSCONSUMPTION

HIGH STAKES, HIGH REWARDS: INTERVENTION DESIGN | 17

However, companies in India still face structural

challenges that impair intervention design. For example,

45% say the biggest roadblock to greater adoption and

consumption of analytics insights is poor integration of

this resource within current processes. The firms also

face personnel problems. More than a third of the Indian

respondents say that the people who need to take the

action do not have the required skills.

Indian firms have an advantage in how extensively senior

leaders embrace advanced analytics. But to further

capitalize on this and other strengths, Indian firms must

make adopting analytics and improving the skills of

people throughout the organization top priorities in the

months ahead.

WHEN IN THE PROCESS DO YOU TYPICALLY DESIGN HOW THE ANALYTICS WILL BE APPLIED (WHAT ACTIONS WILL BE TAKEN TO REALIZE VALUE)?

WHAT PERCENTAGE OF THE TIME DO SENIOR BUSINESS LEADERS INCLUDE DATA ANALYTICS IN THEIR DECISION-MAKING ABOUT DESIGNING AND EXECUTING STRATEGIES?

When we are designing the use case at a high

level

29%

After we have determined what type of analytics will be applied

28%

After we have started data collection and know

what is possible

26%

After we have built models and determined

what insights can be generated

16%

SOONER LATER

0-25%

26%-50% 36%

51%-75% 38%

More than 75% 19%

8%



45%

Business Process

The analytics

insights are not

well integrated

into current

processes

36%

Skills

People who

need to take the

action to not

have the

required skills

31%

Organization

Design

Interaction

between various

people/groups

does not

function well

31%

User

Design

How the

individual

‘interfaces’ with

the analytics is

not well

designed

30%

Data

Data used for

analytics is not

of high quality

or not trusted

24%

Incentives

Actions the

analytics suggest

are not aligned

to current

employee

incentives


WHAT ARE THE BIGGEST CHALLENGES WITH DRIVING ADOPTION/CONSUMPTION OF ANALYTICS INSIGHTS?

1 When business initiatives are being developed, apply

advanced analytics as early as possible—preferably

when designing use cases at a high level. This enables

stakeholders to shape and test the validity of initiatives

based on available data rather than pure instinct.

2 Closely integrate the output of advanced analytics

into business processes. Otherwise, organizations

risk wasting time and resources developing insights

without any assurance of realizing their value.

3 While the growth of predictive analytics and

machine learning may increase reliance on automated

decisions, human insights will remain a vital element

when making strategic and operational decisions.

Continue to invest in resources that support both the

art and science of using analytics effectively.

RECOMMENDATIONS

HIGH STAKES, HIGH REWARDS: MEASUREMENT AND LEARNING | 19

KEY FINDINGS

• Less than a third of Indian firms use well-defined metrics to gauge enterprise-wide performance of advanced analytics

• Indian companies struggle with communicating business outcomes to the stakeholders

• Addressing measurement and communication challenges remains a high priority

In the end, the value of resource investments devoted to

devising and activating advanced analytics strategies must

be evaluated for how well they support desired business

outcomes. But many companies still struggle to quantify

the benefits of data-driven business initiatives. For

example, only 31% of Indian executives say the enterprise-

wide performance of advanced analytics is managed

consistently and use a well-defined set of financial and

non-financial measures. A significant percentage of the

others struggle with delivering consistent performance

measurements across functions and lines of business.

Successfully aligning measurements to the definitions of

business outcomes that were developed during the early

WHICH BEST DESCRIBES HOW VALUE IS MEASURED WHEN DEMONSTRATINGTHE IMPACT OF DATA ANALYTICS ON YOUR ORGANIZATION?

MEASUREMENT AND LEARNING

ANALYTICS CONSUMPTION

OUTCOMES

2%

Performance of analytics is managed consistently globally using

a well-defined set of financial and non-financial measurest

Performance of analytics is measured and managed, but

inconsistent across functions and lines of business

Analytics initiatives are managed as a portfolio with risk weighted

value assessments impacting resource allocation decisions

Definition of business outcomes is typically established

up front, but measurement is often difficult

No visibility into the value created from analytics initiatives

31%

26%

25%

16%


HOW EFFECTIVE IS YOUR ORGANIZATION AT IMPLEMENTING TEST AND LEARN PROCESSES THAT THEN IMPACT ANALYTICS MODELS AND SUGGESTED ACTIONS?

Communication of business outcomes to the stakeholders 36%

Too many factors influence the business outcome (cannot isolate the actions from analytics) 34%

Capturing required data is difficult/too costly 32%

Lack of clear responsibility for business outcomes 30%

Expected performance outcomes are not well defined 27%

Lack of trust in the data 20%

Lack of trust in the measurement process 20%

Don’t know/unsure 1%

Other 0%

WHAT ARE THE BIGGEST CHALLENGES TO MEASURING VALUE REALIZATION?

Highly Ineffective

8%

Ineffective

5%

Neither Ineffective

or Effective

9%

Effective

43%

Highly Effective

35%

HIGH STAKES, HIGH REWARDS: MEASUREMENT AND LEARNING | 21

stages of projects is another trouble spot.

Thirty-five percent of Indian executives say they’re

highly effective at implementing test and learning

processes that then impact analytics models and

suggested actions. But nearly a quarter of their

peers admit to being ineffective or at best say their

effectiveness is a wash.

The underlying reasons for these breakdowns are

varied, and cut across technical and cultural issues.

Indian companies struggle with communicating

business outcomes to the stakeholders. Complexity

is a problem—more than a third say too many factors

influence the business outcome. Financial constraints

are another concern—32% say capturing required data

is difficult or too costly.

Leaders who are responsible for guiding their

organizations to more data-driven cultures must

make addressing measurement and communication

challenges a high priority.

1 Create a strategy for measuring performance

that defines a common language and processes for

collecting and analyzing outcome data.

2 Develop detailed metrics that measure the tangible

results of data-driven business initiatives.

3 Set specific targets for business growth, gains in

revenues and profits, and other important goals, such

as reducing risk. Then continuously track progress

toward reaching these goals.

RECOMMENDATIONS


A FOUNDATIONFOR FUTURE SUCCESS

To stay competitive and remain market leaders in their respective markets,

enterprises everywhere are increasing their commitments and investments in

advanced analytics. Indian leaders are seeing a pay-off from these efforts. In

particular, senior executives in India are more likely than others to replace gut-

feel decision-making with insights gained from their rich data reserves.

However, problems with stakeholder collaboration and corporate-wide

governance policies are holding back the further maturing of advanced

analytics initiatives in the subcontinent. Addressing these shortcomings

must be a top priority for Indian executives going forward—to stay ahead of

competitors globally and use advanced analytics as a strategic advantage for

developing tomorrow’s successful business initiatives.

HIGH STAKES, HIGH REWARDS: CONCLUSION | 23

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© 2017 EYGM Limited. All Rights Reserved.

EYG no. 01096-163GBL

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advice.

The views of third parties set out in this publication are not necessarily the views of the global EY

organization or its member firms. Moreover, they should be viewed in the context of the time they

were made.

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